Automatic Individual Detection and Separation of Multiple Overlapped Nematode Worms Using Skeleton Analysis

摘要

We present a new method for detection and separation of individual nematode worms in a still image. After pre-processing stage, which includes image binarization, filling the small holes, obtaining the skeleton of the new image and pruning the extra branches of skeleton, we split a skeleton into several branches by eliminating the connection pixels (pixels with more than 2 neighbors). Then we compute angles of all branches and compare the angles of the neighboring branches. The neighbor branches with angle differences less than a threshold are connected. Our method has been applied to a database of 54 overlap worms and results in 82% accuracy as automatic and 89% as semi-automatic with some limited user interaction.